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Updated: Jun 16, 2025

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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
Published on: November 3, 2010
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The value-ladenness of ancestry
1Department of Philosophy, Université Du Québec à Montréal, Pavillon Thérèse-Casgrain, 5è étage, 455Boulevard René-Lévesque Est, Local W-5350, H2L 4Y2, Canada.
Studies in History and Philosophy of Science
|June 14, 2025
Summary
Genetic ancestry descriptors in human genomics are not purely objective. This study introduces an axiological approach, revealing that "ancestry" is value-laden, highlighting the role of values in genomics.
Area of Science:
- Human Genomics
- Population Genetics
- Bioethics
Background:
- Clustering human populations by genetic ancestry is standard in genomics.
- Descriptors like "race," "ethnicity," and "genetic ancestry" label these genetically similar groups.
- There's a trend to favor "genetic ancestry" over "race" for perceived objectivity.
Purpose of the Study:
- To propose an axiological framework for understanding population descriptor choices in human genomics.
- To demonstrate that the descriptor "ancestry" is inherently value-laden.
- To establish the validity of incorporating values into the selection and application of genomic population descriptors.
Main Methods:
- Axiological analysis of population descriptor terminology in human genomics.
- Examination of the concept of objectivity in scientific classification.
- Philosophical inquiry into the role of values in scientific practice.
Main Results:
- The descriptor "genetic ancestry" is not objectively neutral but carries inherent values.
- Claims of objectivity for population descriptors do not fully justify their selection and use.
- An axiological perspective reveals the influence of values on genomic classifications.
Conclusions:
- The choice and use of population descriptors in human genomics are influenced by values.
- "Genetic ancestry" is a value-laden term, not a purely objective scientific construct.
- Values play a legitimate and necessary role in the application of population descriptors in genomics.
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